BIOL 701 Likelihood Methods in Biology 2013

The course provides an introduction to likelihood-based inference in Biology. We will cover both theoretical and practical aspects of maximum likelihood and Bayesian inference.
Meeting: Monday and Wednesday 10:00-10:50AM in 2025 Haworth
The syllabus is available as a pdf by clicking here .
Instructors (office hours by appointment):
John Kelly 864-3706 5005 Haworth
Mark Holder 864-5789 6031 Haworth
Grades will be based on class participation and homework assignments. We will have approximately one homework assignment per week.


Date Topic and Links Assignments
Week 1 Jan 23 Probability, random variables, distributions
Week 2 Jan 28, Jan 30 Random samples, sample distributions, likelihood HW1_2013.doc
Week 3 Feb 04, Feb 06 Explicitly specifying variability: likelihood examples and Bayes' rule.
Notes on probability by Bálint Tóth
Week 4 Feb 11, Feb 13 Likelihood examples and maximum likelihood estimation
Week 5 Feb 18, Feb 20 Review / Likelihood ratio test statistic HW3_2013.doc (due Wed., Feb. 27)
Week 6 Feb 25, Feb 27 Generalized Linear Models Mark's notes on the lecture about testing with nuisance parameters
Week 7 Mar 04, Mar 06 Generalized Linear Models (continued) HW4_2013.doc (due March 13)
Week 8 Mar 11, Mar 13 Numerical Optimization/Parametric bootstrapping numerical_opt.pdf notes
num_opt_summary_example_code_intro.pdf Save this as and run using:
python 0.5 1000
You'll need Python and you'll need to install SciPy
Of you can check out the R version generalMismatchedFights.R.txt
which requires the data in a separate file: simpleData.txt
Mar 18 - Mar 22 SPRING BREAK
Week 9 Mar 25, Mar 27 Programming Intro, MCMC Homework5-2013.pdf (due Wed, April 3rd)
Notes: BayesianMCMC-2013.pdf
Week 10 Apr 01, Apr 03 MCMC continued
Week 11 Apr 08, Apr 10 Multiparameter MCMC latent_variable_MCMC.pdf (notes)
See for a Python template.
An R template is at coin_contamination.R it will write files called MCMC-output.txt and MCMC-samples.txt to its working directory.
Code snippet for running Gelman-Rubin diagnostic on tabular MCMC output.
Convergence Diagnostics Notes by Patrick K. Lam .
Week 12 Apr 15, Apr 17 Hastings ratio and model jumping hastingsRatio.pdf
Week 13 Apr 22, Apr 24 MTH's notes on JKK's lecture: source code and pdf The homework from 2011 that we discussed in class is here and this is a link to the GLM ML code that I discussed in class.
Week 14 Apr 29, May 01 Special topics: based on student suggestions Lewis et al paper with reversible jump move. Updated multi_parameter_mcmc.pdf notes.
First part of the last homework: Homework7-2013-preview.pdf
Homework7-2013.pdf (with corrections May 17th)
See (python) or (R) as your language preference dictates.
Week 15 May 06, May 08 Special topics: based on student suggestions